Publication: Detecting Urban Clues for Road Safety: Leveraging Big Data and Machine Learning in World Bank Transport Projects
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2021-11-30
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2022-02-25
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Transportation services and infrastructure connect people, businesses, and places. They allow citizens to access opportunities, such as jobs, education, health services, recreation, and enable the movement and distribution of goods. As a result, transport services and infrastructure are key to the economic development of cities and regions. While the development of transportation systems and infrastructure is vital to economic growth, it is also important to evaluate and mitigate its potential negative externalities and costs to society. The purpose of this guidance note is to provide concrete guidance on how big data and machine learning (ML) can be leveraged in road safety analysis. The document presents opportunities to use these new technologies to improve current road safety assessment procedures across the project cycle, in accordance with the World Bank’s latest Environmental and Social Framework (ESF) guidelines. This guidance note is for World Bank task teams who are interested in using new data sources and analytical methods for road safety analysis across various types of projects. This document consists of three parts. Part 1 discusses the World Bank’s current guidelines for incorporating road safety analysis across the project cycle, examines existing data and approaches and identifies opportunities to improve current methods using big data and ML. Part 2 provides an overview of these new technologies and concrete guidance on how they can be integrated into World Bank projects. Part 3 presents case studies on two regions of interest – Bogotá, Colombia and Padang, Indonesia to demonstrate how ML can be implemented to evaluate road safety. The document concludes with recommendations for using big data and ML in road safety assessments in the future.
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“World Bank. 2021. Detecting Urban Clues for Road Safety: Leveraging Big Data and Machine Learning in World Bank Transport Projects. © World Bank. http://hdl.handle.net/10986/37043 License: CC BY 3.0 IGO.”
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Publication Detecting Urban Clues for Road Safety(Washington, DC: World Bank, 2021-11-30)Transportation services and infrastructure connect people, businesses, and places. They allow citizens to access opportunities, such as jobs, education, health services, recreation, and enable the movement and distribution of goods. As a result, transport services and infrastructure are key to the economic development of cities and regions. The purpose of this guidance note is to provide concrete guidance on how big data and machine learning (ML) can be leveraged in road safety analysis. The document presents opportunities to use these new technologies to improve current methods for data collection and analysis for various road safety assessments. This guidance note provides a practical guide for using new data sources and analytical methods for road safety analysis in different types of projects that may impact road infrastructure or risk-related factors. This document consists of three parts. Part 1 provides an overview of existing approaches and tools for road safety assessment and identifies opportunities to improve these using new technologies such as big data and ML. Part 2 provides an overview of these new technologies and concrete guidance on how they can be integrated into transport projects for road safety analysis. Part 3 presents case studies on two regions of interest – Bogotá, Colombia and Padang, Indonesia to demonstrate how ML can be implemented to evaluate road safety. The document concludes with recommendations for using big data and ML in road safety assessments in the future.Publication Saving Lives Through Private Investment in Road Safety(Washington, DC: World Bank, 2022-02-22)The World Bank estimates a significant funding gap in road safety of 260 billion to achieve SDG 3.6 and 11.2 in the next ten years, and recognizes that this gap cannot be closed through public funding alone and thus mobilization of private capital is required. 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However, according to World Health Organization data the estimated fatality rate in 2016 was 15.9 per 100,000 population, which is nearly double the offi cial estimate. In 2016, vulnerable road users (pedestrians, cyclists, and motorcyclists) accounted for around 72 percent of all road fatality victims, among the highest levels in the region, with pedestrians accounting for half of these. Road deaths have a disproportionate impact on the young, working age population. About 40 percent of people killed on Nepal’s roads in 2017 –18 were less than 26 years old. In 2016, transport injuries were the second leading cause of death among men aged 15–49-years.Publication Road Safety(Washington, DC, 2003-09)In 1999, between 750 000 and 880 000 persons died in road crashes worldwide, and another 23 to 34 million people were injured. The situation is particularly critical in low and middle income countries (LMCs) where about 86 percent of deaths from road traffic injuries occur even though these countries account for only 40 percent of all motor vehicles. The graph shows that the situation has been worsening in LMCs since 1987. There are strong social, health and economic reasons to reduce the burden of road traffic injuries (RTIs): a) casualties affect mostly economically active persons and have a ripple effect on their dependents, causing suffering and poverty; and b) crash victims represent between 30 and 86 percent of all trauma admissions. They tend to stay in hospital longer than average patients. Developed countries have been relatively successful in reducing the burden of RTIs. This shows that more, better targeted and sustainable investment can prevent RTIs and reduce the damage that results from crashes. Poorer countries clearly need a new and broader approach to road safety.
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